The present invention relates generally to automatic defect recognition (ADR) and more particularly to an improved methodology that employs a sequential approach to automatic defect recognition.
Automatic defect recognition (ADR) is an important component of nondestructive testing (NDT) techniques in the detection, classification or assessment of significant flaws or irregularities in manufacturing parts or objects of interest. Example of significant flaws in manufactured parts includes a defect size, shape, composition or other relevant characteristic that falls outside of the range of acceptable variability for a given structure or object of interest. Conventional ADR methods and systems call for the use of sophisticated image analysis algorithms. However, such algorithms are usually slow, and the usability of ADR systems is restricted by the ensuing trade-off between detection and computational performances. The typical solutions the industry has adopted to the problem of designing effective and efficient ADR algorithms are: accepting a limitation in effectiveness by the use of simple and fast algorithms; and adopting off-line inspection by sampling, a procedure which has much lower efficiency requirements but does not allow for inspection of every single part. Either one of these solutions can be accompanied by the use of specialized hardware to enable faster computations.
The use of image-based ADR systems in a production line often requires strict processing-time specifications. On the other hand, the typical high-performance requirements of such systems calls for the use of sophisticated, computationally-complex algorithms. Addressing the conflicting requirements of fast throughput and high detection performance at low false-alarm rates is a significant challenge.
Accordingly, there is a need for improving upon current ADR methodologies.